High capacity in G protein-coupled receptor signaling

Lactobacilli-Mediated Regulation of the Microbial-Immune Axis: A Review of Key Mechanisms, Influencing Factors, and Application Prospects

Lactobacilli, as the main member of food microorganisms, is an important component of the intestinal microbial community and plays crucial roles in regulating the immune capacity of the body. This review provides a comprehensive exploration of the key components of Lactobacilli-mediated immune regulation effects, including the immunogenic components (peptidoglycan and lipoteichoic acid) and metabolites (short-chain fatty acids, bacteriocins, and exopolysaccharides), which can interact with host immune cell receptors to initiate complex immune signaling pathways. In addition, the immunomodulatory activity can be influenced by multiple factors including species differences, host-related factors (age, physiological conditions, and gut microbiota), and environmental factors (nutrient substrates, temperatures, etc.), and the application strategies including precision probiotic development, gene-editing driven engineering, and nanocarrier systems have also been proposed to enhance the immunomodulatory potential. Finally, this review provides the theoretical basis for microbial intervention in immune-related diseases and offers prospects for applications in the food and pharmaceutical industries.

Individual yeast cells signal at different levels but each with good precision

Different isogenic cells exhibit different responses to the same extracellular signals. Several authors assumed that this variation arose from stochastic signalling noise with the implication that single eukaryotic cells could not detect their surroundings accurately, but work by us and others has shown that the variation is dominated instead by persistent cell-to-cell differences. Here, we analysed previously published data to quantify the sources of variation in pheromone-induced gene expression in Saccharomyces cerevisiae. We found that 91% of response variation was due to stable cell-to-cell differences, 8% from experimental measurement error, and 1% from signalling noise and expression noise. Low noise enabled precise signalling; individual cells could transmit over 3 bits of information through the pheromone response system and so respond differently to eight different pheromone concentrations. Additionally, if individual cells could reference their responses against constitutively expressed proteins, then cells could determine absolute pheromone concentrations with 2 bits of accuracy. These results help explain how individual yeast cells can accurately sense and respond to different extracellular pheromone concentrations.

A New Era of Muscarinic Acetylcholine Receptor Modulators in Neurological Diseases, Cancer and Drug Abuse

The cholinergic pathways in the central nervous system (CNS) play a pivotal role in different cognitive functions of the brain, such as memory and learning. This review takes a dive into the pharmacological side of this important part of CNS function, taking into consideration muscarinic receptors and cholinesterase enzymes. Targeting a specific subtype of five primary muscarinic receptor subtypes (M1-M5) through agonism or antagonism may benefit patients; thus, there is a great pharmaceutical research interest. Inhibition of AChE and BChE, orthosteric or allosteric, or partial agonism of M1 mAChR are correlated with Alzheimer's disease (AD) symptoms improvement. Agonism or antagonism on different muscarinic receptor subunits may lessen schizophrenia symptoms (especially positive allosteric modulation of M4 mAChR). Selective antagonism of M4 mAChR is a promising treatment for Parkinson's disease and dystonia, and the adverse effects are limited compared to inhibition of all five mAChR. Additionally, selective M5 antagonism plays a role in drug independence behavior. M3 mAChR overexpression is associated with malignancies, and M3R antagonists seem to have a therapeutic potential in cancer, while M1R and M2R inhibition leads to reduction of neoangiogenesis. Depending on the type of cancer, agonism of mAChR may promote cancer cell proliferation (as M3R agonism does) or protection against further tumor development (M1R agonism). Thus, there is an intense need to discover new potent compounds with specific action on muscarinic receptor subtypes. Chemical structures, chemical modification of function groups aiming at action enhancement, reduction of adverse effects, and optimization of Drug Metabolism and Pharmacokinetics (DMPK) will be further discussed, as well as protein-ligand docking.

MSR1-dependent efferocytosis improved ischemia-reperfusion injury following aged-donor liver transplantation in mice by regulating the pro-resolving polarisation of macrophages

Compared with young liver donors, aged liver donors are more susceptible to ischemia-reperfusion injury (IRI) following transplantation, which may be related to excessive inflammatory response and macrophage dysfunction, but the specific mechanism is unclear. Macrophage scavenger receptor 1 (MSR1) is a member of the scavenger receptor family, and plays an important regulatory role in inflammation response and macrophage function regulation. But its role in IRI following aged-donor liver transplantation is still unclear. This study demonstrates that MSR1 expression is decreased in macrophages from aged donor livers, inhibiting their efferocytosis and pro-resolving polarisation. Decreased MSR1 is responsible for the more severe IRI suffered by aged donor livers. Overexpression of MSR1 using F4/80-labelled AAV9 improved intrahepatic macrophage efferocytosis and promoted pro-resolving polarisation, ultimately ameliorating IRI following aged-donor liver transplantation. In vitro co-culture experiments further showed that overexpression of MSR1 promoted an increase in calcium concentration, which further activated the PI3K-AKT-GSK3β pathway, and induced the upregulation of β-catenin. Overall, MSR1-dependent efferocytosis promoted the pro-resolving polarisation of macrophages through the PI3K-AKT-GSK3β pathway-induced up-regulating of β-catenin leading to improved IRI following aged-donor liver transplantation.

Characterizing heterogeneous single-cell dose responses computationally and experimentally using threshold inhibition surfaces and dose-titration assays

Single cancer cells within a tumor exhibit variable levels of resistance to drugs, ultimately leading to treatment failures. While tumor heterogeneity is recognized as a major obstacle to cancer therapy, standard dose-response measurements for the potency of targeted kinase inhibitors aggregate populations of cells, obscuring intercellular variations in responses. In this work, we develop an analytical and experimental framework to quantify and model dose responses of individual cancer cells to drugs. We first explore the connection between population and single-cell dose responses using a computational model, revealing that multiple heterogeneous populations can yield nearly identical population dose responses. We demonstrate that a single-cell analysis method, which we term a threshold inhibition surface, can differentiate among these populations. To demonstrate the applicability of this method, we develop a dose-titration assay to measure dose responses in single cells. We apply this assay to breast cancer cells responding to phosphatidylinositol-3-kinase inhibition (PI3Ki), using clinically relevant PI3Kis on breast cancer cell lines expressing fluorescent biosensors for kinase activity. We demonstrate that MCF-7 breast cancer cells exhibit heterogeneous dose responses with some cells requiring over ten-fold higher concentrations than the population average to achieve inhibition. Our work reimagines dose-response relationships for cancer drugs in an emerging paradigm of single-cell tumor heterogeneity.

Information Transmission in G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are the largest class of receptors in the human genome and constitute about 30% of all drug targets. In this article, intended for a non-mathematical audience, both experimental observations and new theoretical results are compared in the context of information transmission across the cell membrane. The amount of information actually currently used or projected to be used in clinical settings is a small fraction of the information transmission capacity of the GPCR. This indicates that the number of yet undiscovered drug targets within GPCRs is much larger than what is currently known. Theoretical studies with some experimental validation indicate that localized heat deposition and dissipation are key to the identification of sites and mechanisms for drug action.

The ability to sense the environment is heterogeneously distributed in cell populations

Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information theoretic framework to quantify the distribution of sensing abilities from single cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an " average cell ". We verify these predictions using live cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells' sensing abilities. This information theoretic framework will significantly improve our understanding of how cells sense in their environment.

Interplay between G protein-coupled receptors and nanotechnology

G protein-coupled receptors (GPCRs), as the largest family of membrane receptors, actively modulate plasma membrane and endosomal signalling. Importantly, GPCRs are naturally nanosized, and spontaneously formed nanoaggregates of GPCRs (natural nano-GPCRs) may enhance GPCR-related signalling and functions. Although GPCRs are the molecular targets of the majority of marketed drugs, the poor pharmacokinetics and physicochemical properties of GPCR ligands greatly limit their clinical applicability. Nanotechnology, as versatile techniques, can encapsulate GPCR ligands to assemble synthetic nano-GPCRs to overcome their obstacles, robustly elevating drug efficacy and safety. Moreover, endosomal delivery of GPCR ligands by nanoparticles can precisely initiate sustained endosomal signal transduction, while nanotechnology has been widely utilized for isolation, diagnosis, and detection of GPCRs. In turn, due to overexpression of GPCRs on the surface of various types of cells, GPCR ligands can endow nanoparticles with active targeting capacity for specific cells via ligand-receptor binding and mediate receptor-dependent endocytosis of nanoparticles. This significantly enhances the potency of nanoparticle delivery systems. Therefore, emerging evidence has revealed the interplay between GPCRs and nanoparticles, although investigations into their relationship have been inadequate. This review aims to summarize the interaction between GPCRs and nanotechnology for understanding their mutual influences and utilizing their interplay for biomedical applications. It will provide a fundamental platform for developing powerful and safe GPCR-targeted drugs and nanoparticle systems. STATEMENT OF SIGNIFICANCE: GPCRs as molecular targets for the majority of marketed drugs are naturally nanosized, and even spontaneously form nano aggregations (nano-GPCRs). Nanotechnology has also been applied to construct synthetic nano-GPCRs or detect GPCRs, while endosomal delivery of GPCR ligands by nanoparticles can magnify endosomal signalling. Meanwhile, molecular engineering of nanoparticles with GPCRs or their ligands can modulate membrane binding and endocytosis, powerfully improving the efficacy of nanoparticle system. However, there are rare summaries on the interaction between GPCRs and nanoparticles. This review will not only provide a versatile platform for utilizing nanoparticles to modulate or detect GPCRs, but also facilitate better understanding of the designated value of GPCRs for molecular engineering of biomaterials with GPCRs in therapeutical application.

Improved approaches to channel capacity estimation discover compromised GPCR signaling in diverse cancer cells

Intracellular signaling orchestrates an organism's development and functioning and underlies various pathologies, such as cancer, when aberrant. A universal cell signaling characteristic is channel capacity - the measure of how much information a given transmitting system can reliably transduce. Here, we describe improved approaches to quantify GPCR signaling channel capacity in single cells, averaged across cell population. We assess the channel capacity based on distribution of residuals by the cellular response amplitude. We further develop means to handle irregularly responding cancer cells using the integral values of their response to different agonist concentrations. These approaches enabled us to analyze, for the first time, channel capacity in single cancer cells. A universal feature emerging for different cancer cell types is a decreased channel capacity of their GPCR signaling. These findings provide experimental validation to the hypothesis that cancer is an information disease, bearing importance for basic cancer biology and anticancer drug discovery.

Calcium dysregulation combined with mitochondrial failure and electrophysiological maturity converge in Parkinson's iPSC-dopamine neurons

Parkinson's disease (PD) is characterized by a progressive deterioration of motor and cognitive functions. Although death of dopamine neurons is the hallmark pathology of PD, this is a late-stage disease process preceded by neuronal dysfunction. Here we describe early physiological perturbations in patient-derived induced pluripotent stem cell (iPSC)-dopamine neurons carrying the GBA-N370S mutation, a strong genetic risk factor for PD. GBA-N370S iPSC-dopamine neurons show an early and persistent calcium dysregulation notably at the mitochondria, followed by reduced mitochondrial membrane potential and oxygen consumption rate, indicating mitochondrial failure. With increased neuronal maturity, we observed decreased synaptic function in PD iPSC-dopamine neurons, consistent with the requirement for ATP and calcium to support the increase in electrophysiological activity over time. Our work demonstrates that calcium dyshomeostasis and mitochondrial failure impair the higher electrophysiological activity of mature neurons and may underlie the vulnerability of dopamine neurons in PD.

Model of ligand-triggered information transmission in G-protein coupled receptor complexes

We present a model for the effects of ligands on information transmission in G-Protein Coupled Receptor (GPCR) complexes. The model is built ab initio entirely on principles of statistical mechanics and tenets of information transmission theory and was validated in part using agonist-induced effector activity and signaling bias for the angiotensin- and adrenergic-mediated signaling pathways, with in vitro observations of phosphorylation sites on the C tail of the GPCR complex, and single-cell information-transmission experiments. The model extends traditional kinetic models that form the basis for many existing models of GPCR signaling. It is based on maximizing the rates of entropy production and information transmission through the GPCR complex. The model predicts that (1) phosphatase-catalyzed reactions, as opposed to kinase-catalyzed reactions, on the C-tail and internal loops of the GPCR are responsible for controlling the signaling activity, (2) signaling favors the statistical balance of the number of switches in the ON state and the number in the OFF state, and (3) biased-signaling response depends discontinuously on ligand concentration.

An optimized reporter of the transcription factor hypoxia-inducible factor 1α reveals complex HIF-1α activation dynamics in single cells

Immune cells adopt a variety of metabolic states to support their many biological functions, which include fighting pathogens, removing tissue debris, and tissue remodeling. One of the key mediators of these metabolic changes is the transcription factor hypoxia-inducible factor 1α (HIF-1α). Single-cell dynamics have been shown to be an important determinant of cell behavior; however, despite the importance of HIF-1α, little is known about its single-cell dynamics or their effect on metabolism. To address this knowledge gap, here we optimized a HIF-1α fluorescent reporter and applied it to study single-cell dynamics. First, we showed that single cells are likely able to differentiate multiple levels of prolyl hydroxylase inhibition, a marker of metabolic change, via HIF-1α activity. We then applied a physiological stimulus known to trigger metabolic change, interferon-γ, and observed heterogeneous, oscillatory HIF-1α responses in single cells. Finally, we input these dynamics into a mathematical model of HIF-1α-regulated metabolism and discovered a profound difference between cells exhibiting high versus low HIF-1α activation. Specifically, we found cells with high HIF-1α activation are able to meaningfully reduce flux through the tricarboxylic acid cycle and show a notable increase in the NAD+/NADH ratio compared with cells displaying low HIF-1α activation. Altogether, this work demonstrates an optimized reporter for studying HIF-1α in single cells and reveals previously unknown principles of HIF-1α activation.

Identification of molecular initiating events and key events leading to endocrine disrupting effects of PFOA: Integrated molecular dynamic, transcriptomic, and proteomic analyses

Perfluorooctanoic acid (PFOA) can rapidly activate signaling pathways independent of nuclear hormone receptors through membrane receptor regulation, which leads to endocrine disrupting effects. In the present work, the molecular initiating event (MIE) and the key events (KEs) which cause the endocrine disrupting effects of PFOA have been explored and determined based on molecular dynamics simulation (MD), fluorescence analysis, transcriptomics, and proteomics. MD modeling and fluorescence analysis proved that, on binding to the G protein-coupled estrogen receptor-1 (GPER), PFOA could induce a conformational change in the receptor, turning it into an active state. The results also indicated that the binding to GPER was the MIE that led to the adverse outcome (AO) of PFOA. In addition, the downstream signal transduction pathways of GPER, as regulated by PFOA, were further investigated through genomics and proteomics to identify the KEs leading to thr endocrine disrupting effects. Two pathways (Endocrine resistance, ERP and Estrogen signaling pathway, ESP) containing GPER were regulated by different concentration of PFOA and identified as the KEs. The knowledge of MIE, KEs, and AO of PFOA is necessary to understand the links between PFOA and the possible pathways that lead to its negative effects.

A genetic platform for functionally profiling odorant receptors in olfactory cilia ex vivo

The molecular basis for odor perception in humans remains enigmatic because of the difficulty in studying odorant receptors (ORs) outside their native environment. Efforts toward OR expression and functional profiling have been met with limited success because of the poor efficiency of their cell surface expression in vitro. Structures protruding from the surface of olfactory sensory neurons called cilia contain all of the components of the olfactory signal transduction machinery and can be placed in an ex vivo plate assay to rapidly measure odor-specific responses. Here, we describe an approach using cilia isolated from the olfactory sensory neurons of mice expressing two human ORs, OR1A1 and OR5AN1, that showed 10- to 100-fold more sensitivity to ligands as compared to previous assays. A single mouse can produce enough olfactory cilia for up to 4000 384-well assay wells, and isolated cilia can be stored frozen and thus preserved. This pipeline offers a sensitive and highly scalable ex vivo odor-screening platform that has the potential to decode human olfaction.

Histamine/H1 receptor signaling in the parafacial region increases activity of chemosensitive neurons and respiratory activity in rats

Histaminergic neurons of the tuberomammillary nucleus (TMN) are pH-sensitive and contribute to CO₂/H⁺-dependent behaviors including arousal and respiratory activity. TMN neurons project to several respiratory centers including the ventral parafacial region (pF) where chemosensitive retrotrapezoid (RTN) neurons are located, and since RTN neurons are an important source of CO₂/H⁺-dependent respiratory drive, we wondered whether histamine contributes to RTN chemoreception. To test this, we characterized effects of histamine on mean arterial pressure (MAP) and diaphragm muscle activity (DIA_EMG) in urethane-anaesthetized, vagotomized and artificially ventilated male Wistar rats. Unilateral injection of histamine (25 mM) in the pF increased DIA_EMG amplitude without changing DIA_EMG frequency and MAP. Bilateral pF injections of the H1 receptor antagonist diphenhydramine hydrochloride (DPH; 0.5 mM) decreased baseline DIA_EMG amplitude and frequency and MAP. Despite the strong inhibitory effect of DPH on baseline breathing, the hypercapnic ventilatory response was preserved under these experimental conditions. At the cellular level, chemosensitive RTN neurons showed a dose-dependent excitatory response to histamine that was blunted by DPH and mimicked by the H1 receptor agonist 2-pyridylethylamine dihydrochloride (2PYEA) under both control conditions and when fast neurotransmitter receptors are blocked. We also tested effects of 2PYEA in the presence of serotonin, another wake-on neurotransmitter that activates RTN chemoreceptors partly by activation of Gq-coupled receptors. We found the response to 2PYEA was diminished in serotonin, suggesting RTN neurons have a limited capacity to respond to multiple Gq-coupled modulators. These results suggest histamine can modulate breathing at the pF level by a mechanism involving H1 receptors.

Histamine via histamine H1 receptor enhances the muscarinic receptor-induced calcium response to acetylcholine in an enterochromaffin cell model

As a prerequisite for serotonin secretion, the P‐STS ileal enterochromaffin cell line responds to acetylcholine (ACh) stimulation with an increase in intracellular calcium mediated by the muscarinic ACh receptor M3 (M3R). Histamine increases intracellular calcium via histamine H1 receptor (H1R) in P‐STS cells and pre‐incubation with histamine specifically augments the response to ACh but not to epinephrine or nicotine. We aimed to elucidate whether histamine receptors are involved in this synergism. Astonishingly, HEK‐293 T cells—known to express M3R, but only a very low amount of histamine receptor messenger RNA—showed a similar enhancement of the calcium response to ACh by pre‐incubation with histamine. Despite the much lower level of H1R protein detected in HEK‐293 T cells as compared to P‐STS cells, in both cell lines pre‐treatment with H1R antagonists inhibited the synergism between histamine and ACh. No indication for an involvement of histamine H2 or H4 receptors in the synergism was found. Furthermore, pre‐incubation with the cAMP‐inducing compound forskolin had no influence on the intracellular calcium response to ACh. Serotonin secretion from P‐STS cells was increased after challenge with ACh and histamine added simultaneously compared to ACh alone, suggesting that histamine increases ACh‐induced serotonin secretion from enterochromaffin cells. In conclusion, our data suggest that histamine enhances the M3R‐mediated intracellular calcium response to ACh via activation of H1R. This probably increases serotonin secretion from enterochromaffin cells and thereby affects intestinal motility in histamine intolerance, food allergies and irritable bowel syndrome.

Phenotypic variability, not noise, accounts for most of the cell-to-cell heterogeneity in IFN-γ and oncostatin M signaling responses

Cellular signaling responses show substantial cell-to-cell heterogeneity, which is often ascribed to the inherent randomness of biochemical reactions, termed molecular noise, wherein high noise implies low signaling fidelity. Alternatively, heterogeneity could arise from differences in molecular content between cells, termed molecular phenotypic variability, which does not necessarily imply imprecise signaling. The contribution of these two processes to signaling heterogeneity is unclear. Here, we fused fibroblasts to produce binuclear syncytia to distinguish noise from phenotypic variability in the analysis of cytokine signaling. We reasoned that the responses of the two nuclei within one syncytium could approximate the signaling outcomes of two cells with the same molecular content, thereby disclosing noise contribution, whereas comparison of different syncytia should reveal contribution of phenotypic variability. We found that ~90% of the variance in the primary response (which was the abundance of phosphorylated, nuclear STAT) to stimulation with the cytokines interferon-γ and oncostatin M resulted from differences in the molecular content of individual cells. Thus, our data reveal that cytokine signaling in the system used here operates in a reproducible, high-fidelity manner.

Functional Rescue of a Nephrogenic Diabetes Insipidus Causing Mutation in the V2 Vasopressin Receptor by Specific Antagonist and Agonist Pharmacochaperones

The urine concentrating function of the kidney is essential to maintain the water homeostasis of the human body. It is mainly regulated by the arginine-vasopressin (AVP), which targets the type 2 vasopressin receptor (V2R) in the kidney. The inability of V2R to respond to AVP stimulation leads to decreased urine concentration and congenital nephrogenic diabetes insipidus (NDI). NDI is characterized by polyuria, polydipsia, and hyposthenuria. In this study, we identified a point mutation (S127F) in the AVPR2 gene of an NDI patient, and we characterized the impaired function of the V2R mutant in HEK293 cells. Based on our data, the S127F-V2R mutant is almost exclusively located intracellularly in the endoplasmic reticulum (ER), and very few receptors were detected at the cell surface, where the receptor can bind to AVP. The overexpressed S127F-V2R mutant receptor has negligible cAMP generation capability compared to the wild-type receptor in response to AVP stimulation. Since certain misfolded mutant proteins, that are retained in the ER, can be rescued by pharmacological chaperones, we examined the potential rescue effects of two pharmacochaperones on the S127F-V2R. We found that pretreatment with both tolvaptan (an established V2R inverse agonist) and MCF14 compound (a cell-permeable high-affinity agonist for the V2R) were capable of partially restoring the cAMP generating function of the receptor in response to vasopressin stimulation. According to our data, both cell permeant agonists and antagonists can function as pharmacochaperones, and serve as the starting compounds to develop medicines for patients carrying the S127F mutation.

Cellular Signaling beyond the Wiener-Kolmogorov Limit

Accurate propagation of signals through stochastic biochemical networks involves significant expenditure of cellular resources. The same is true for regulatory mechanisms that suppress fluctuations in biomolecular populations. Wiener-Kolmogorov (WK) optimal noise filter theory, originally developed for engineering problems, has recently emerged as a valuable tool to estimate the maximum performance achievable in such biological systems for a given metabolic cost. However, WK theory has one assumption that potentially limits its applicability: it relies on a linear, continuum description of the reaction dynamics. Despite this, up to now no explicit test of the theory in nonlinear signaling systems with discrete molecular populations has ever seen performance beyond the WK bound. Here we report the first direct evidence of the bound being broken. To accomplish this, we develop a theoretical framework for multilevel signaling cascades, including the possibility of feedback interactions between input and output. In the absence of feedback, we introduce an analytical approach that allows us to calculate exact moments of the stationary distribution for a nonlinear system. With feedback, we rely on numerical solutions of the system's master equation. The results show WK violations in two common network motifs: a two-level signaling cascade and a negative feedback loop. However, the magnitude of the violation is biologically negligible, particularly in the parameter regime where signaling is most effective. The results demonstrate that while WK theory does not provide strict bounds, its predictions for performance limits are excellent approximations, even for nonlinear systems.

Computer vision reveals hidden variables underlying NF-κB activation in single cells

Individual cells are heterogeneous when responding to environmental cues. Under an external signal, certain cells activate gene regulatory pathways, while others completely ignore that signal. Mechanisms underlying cellular heterogeneity are often inaccessible because experiments needed to study molecular states destroy the very states that we need to examine. Here, we developed an image-based support vector machine learning model to uncover variables controlling activation of the immune pathway nuclear factor κB (NF-κB). Computer vision analysis predicts the identity of cells that will respond to cytokine stimulation and shows that activation is predetermined by minute amounts of “leaky” NF-κB (p65:p50) localization to the nucleus. Mechanistic modeling revealed that the ratio of NF-κB to inhibitor of NF-κB predetermines leakiness and activation probability of cells. While cells transition between molecular states, they maintain their overall probabilities for NF-κB activation. Our results demonstrate how computer vision can find mechanisms behind heterogeneous single-cell activation under proinflammatory stimuli.

A molecular communication channel consisting of a single reversible chain of hydrogen bonds in a conformationally flexible oligomer

Communication of information through the global switching of conformation in synthetic molecules has hitherto entailed the inversion of chirality. Here, we report a class of oligomer through which information may be communicated through a global reversal of polarity. Ethylene-bridged oligoureas are constitutionally symmetrical, conformationally flexible molecules organized by a single chain of hydrogen bonds running the full length of the oligomer. NMR reveals that this hydrogen-bonded chain may undergo a coherent reversal of directionality. The directional uniformity of the hydrogen-bond chain allows it to act as a channel for the spatial communication of information on a molecular scale. A binding site at the terminus of an oligomer detects local information about changes in pH or anion concentration and transmits that information—in the form of a directionality switch in the hydrogen-bond chain—to a remote polarity-sensitive fluorophore. This propagation of polarity-encoded information provides a new mechanism for molecular communication.

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Simple urea oligomers organize themselves with a single coherent hydrogen-bond chain

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Reversing the polarity of the hydrogen bonding sends a message through the molecule

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Conformational messages can be transmitted by changes in pH or by anion binding

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Receipt of the conformational message is indicated by a remote fluorescent response

Despite the progress made by synthetic chemistry in building the molecular structures of nature, there are still domains of molecular science where biology is immensely more sophisticated than even the most advanced artificial chemical systems. One of these is the ability to use molecular structures to encode and communicate information. Nature stores information in the hydrogen-bond polarity of the base pairs and translates it into molecular function using the polarity matching of these bonds. Here, we outline an early step toward replicating this ability in the design, synthesis, and operation of a series of synthetic molecular devices that employ a structurally simple family of oligomeric molecules that can communicate information in the form of hydrogen-bond polarity. This study marks a significant step in the design of molecular systems that manipulate information, which will form the basis of the many compartmentalization-based nanotechnologies of the future.

Fractional response analysis reveals logarithmic cytokine responses in cellular populations

Although we can now measure single-cell signaling responses with multivariate, high-throughput techniques our ability to interpret such measurements is still limited. Even interpretation of dose–response based on single-cell data is not straightforward: signaling responses can differ significantly between cells, encompass multiple signaling effectors, and have dynamic character. Here, we use probabilistic modeling and information-theory to introduce fractional response analysis (FRA), which quantifies changes in fractions of cells with given response levels. FRA can be universally performed for heterogeneous, multivariate, and dynamic measurements and, as we demonstrate, quantifies otherwise hidden patterns in single-cell data. In particular, we show that fractional responses to type I interferon in human peripheral blood mononuclear cells are very similar across different cell types, despite significant differences in mean or median responses and degrees of cell-to-cell heterogeneity. Further, we demonstrate that fractional responses to cytokines scale linearly with the log of the cytokine dose, which uncovers that heterogeneous cellular populations are sensitive to fold-changes in the dose, as opposed to additive changes.

Our ability to interpret single-cell multivariate signaling responses is still limited. Here the authors introduce fractional response analysis (FRA), involving fractional cell counting, capable of deconvoluting heterogeneous multivariate responses of cellular populations.

Computational methods for characterizing and learning from heterogeneous cell signaling data

Heterogeneity in cell signaling pathways is increasingly appreciated as a fundamental feature of cell biology and a driver of clinically relevant disease phenotypes. Understanding the causes of heterogeneity, the cellular mechanisms used to control heterogeneity, and the downstream effects of heterogeneity in single cells are all key obstacles for manipulating cellular populations and treating disease. Recent advances in genetic engineering, including multiplexed fluorescent reporters, have provided unprecedented measurements of signaling heterogeneity, but these vast data sets are often difficult to interpret, necessitating the use of computational techniques to extract meaning from the data. Here, we review recent advances in computational methods for extracting meaning from these novel data streams. In particular, we evaluate how machine learning methods related to dimensionality reduction and classification can identify structure in complex, dynamic datasets, simplifying interpretation. We also discuss how mechanistic models can be merged with heterogeneous data to understand the underlying differences between cells in a population. These methods are still being developed, but the work reviewed here offers useful applications of specific analysis techniques that could enable the translation of single-cell signaling data to actionable biological understanding.

Single-Cell Information Analysis Reveals That Skeletal Muscles Incorporate Cell-to-Cell Variability as Information Not Noise

Cell-to-cell variability in signal transduction in biological systems is often considered noise. However, intercellular variation (i.e., cell-to-cell variability) has the potential to enable individual cells to encode different information. Here, we show that intercellular variation increases information transmission of skeletal muscle. We analyze the responses of multiple cultured myotubes or isolated skeletal muscle fibers as a multiple-cell channel composed of single-cell channels. We find that the multiple-cell channel, which incorporates intercellular variation as information, not noise, transmitted more information in the presence of intercellular variation than in the absence according to the "response diversity effect," increasing in the gradualness of dose response by summing the cell-to-cell variable dose responses. We quantify the information transmission of human facial muscle contraction during intraoperative neurophysiological monitoring and find that information transmission of muscle contraction is comparable to that of a multiple-cell channel. Thus, our data indicate that intercellular variation can increase the information capacity of tissues.

Constitutive activity of GPR26 regulated by ubiquitin-dependent degradation and its antitumor role

G protein-coupled receptors (GPCRs) play important roles in many physiological functions and numerous diseases. In addition to the classic ligand-stimulated receptor activity, an increasing number of studies have established that many GPCRs function constitutively in a receptor dose-dependent manner. Previous observations showed that following gene transfection, little or no protein was detectable for certain GPCRs (designated apparent state A), such as GPR26, GPR39, GPR78, GPR133, GPR139, BRS3, and LGR5, which showed strong constitutive activities. When we lysed cells in the immediate presence of western blot loading buffer, a significant increase of protein levels was detected (actual state B), which was much closer to the true expression levels under physiological conditions. GPR26 was chosen for further functional experiments as the actual state B. We identified an important ubiquitination site, K286, as well as the ubiquitin ligase E3 homologous to the E6-associated protein carboxyl terminus domain containing 3 interacting with GPR26. The pronounced differences in the protein expression and constitutive activity of GPR26 were a consequence of the ubiquitin-mediated rapid degradation mechanism. Furthermore, we identified in vitro and in vivo antitumor activity associated with high expression levels and constitutive activity of GPR26 in liver cancer cells. Hence, GPR26 could act as an antitumor gene for hepatocellular carcinoma. This study also represents the actual state B of a batch of GPCRs that actually play potentially important roles in physiological functions by their constitutive activity, which is controlled by rapid ubiquitin-dependent degradation.

The Effect of Deuteration on the H2 Receptor Histamine Binding Profile: A Computational Insight into Modified Hydrogen Bonding Interactions

We used a range of computational techniques to reveal an increased histamine affinity for its H₂ receptor upon deuteration, which was interpreted through altered hydrogen bonding interactions within the receptor and the aqueous environment preceding the binding. Molecular docking identified the area between third and fifth transmembrane α-helices as the likely binding pocket for several histamine poses, with the most favorable binding energy of −7.4 kcal mol⁻¹ closely matching the experimental value of −5.9 kcal mol⁻¹. The subsequent molecular dynamics simulation and MM-GBSA analysis recognized Asp98 as the most dominant residue, accounting for 40% of the total binding energy, established through a persistent hydrogen bonding with the histamine −NH₃⁺ group, the latter further held in place through the N–H∙∙∙O hydrogen bonding with Tyr250. Unlike earlier literature proposals, the important role of Thr190 is not evident in hydrogen bonds through its −OH group, but rather in the C–H∙∙∙π contacts with the imidazole ring, while its former moiety is constantly engaged in the hydrogen bonding with Asp186. Lastly, quantum-chemical calculations within the receptor cluster model and utilizing the empirical quantization of the ionizable X–H bonds (X = N, O, S), supported the deuteration-induced affinity increase, with the calculated difference in the binding free energy of −0.85 kcal mol⁻¹, being in excellent agreement with an experimental value of −0.75 kcal mol⁻¹, thus confirming the relevance of hydrogen bonding for the H₂ receptor activation.

An information theoretic approach to insulin sensing by human kidney podocytes

Podocytes are key components of the glomerular filtration barrier (GFB). They are insulin-responsive but can become insulin-resistant, causing features of the leading global cause of kidney failure, diabetic nephropathy. Insulin acts via insulin receptors to control activities fundamental to GFB integrity, but the amount of information transferred is unknown. Here we measure this in human podocytes, using information theory-derived statistics that take into account cell-cell variability. High content imaging was used to measure insulin effects on Akt, FOXO and ERK. Mutual Information (MI) and Channel Capacity (CC) were calculated as measures of information transfer. We find that insulin acts via noisy communication channels with more information flow to Akt than to ERK. Information flow estimates were increased by consideration of joint sensing (ERK and Akt) and response trajectory (live cell imaging of FOXO1-clover translocation). Nevertheless, MI values were always <1Bit as most information was lost through signaling. Constitutive PI3K activity is a predominant feature of the system that restricts the proportion of CC engaged by insulin. Negative feedback from Akt supressed this activity and thereby improved insulin sensing, whereas sensing was robust to manipulation of feedforward signaling by inhibiting PI3K, PTEN or PTP1B. The decisions made by individual podocytes dictate GFB integrity, so we suggest that understanding the information on which the decisions are based will improve understanding of diabetic kidney disease and its treatment.

CAMKK2-CAMK4 signaling regulates transferrin trafficking, turnover, and iron homeostasis

Background

Circulatory iron is a hazardous biometal. Therefore, iron is transported in a redox-safe state by a serum glycoprotein - transferrin (TF). Different organs acquire iron from the systemic circulation through a tightly regulated mechanism at the blood-tissue interface which involves receptor-mediated internalization of TF. Thus, abnormal TF trafficking may lead to iron dyshomeostasis associated with several diseases including neurodegeneration. Iron -induced toxicity can cause neuronal damage to iron-sensitive brain regions. Recently, it was discovered that CAMKK2, a calcium (Ca²⁺)/calmodulin-activated kinase, controls receptor-mediated TF trafficking in mouse tissues, specifically in the brain. The biological function of CAMKK2 is mediated through multiple downstream effectors. Both CAMKK2 and one of its downstream kinase, CAMK4, exhibit overlapping expression in mouse brain. The role of CAMK4 in vesicular transport has been reported and loss of CAMKK2 or CAMK4 leads to cognitive defects in mouse. Therefore, it was hypothesized that CAMKK2-CAMK4 signaling regulates receptor-mediated TF trafficking and iron homeostasis which may be responsible for the neuronal malfunction observed in CAMKK2- or CAMK4-deficient mice.

Methods

CAMK4^−/− mouse was used to study tissue-specific turnover of TF, TF-receptor (TFRC) and iron. CRISPR/Cas9-based CAMKK2 and/or CAMK4 deleted human embryonic kidney-derived HEK293 cell clones were used to study the molecular defects in receptor-mediated TF trafficking. Further, a “zero functional G protein” condition in HEK293 cell was exploited to study CAMKK2-CAMK4 signaling-mediated regulation of intracellular Ca²⁺ homeostasis which was linked to calcium signaling during TF trafficking.

Results

Loss of CAMK4 leads to abnormal post-translational modifications (PTMs) and turnover of TF in mouse cerebellum and liver which was associated with iron dyshomeostasis in these tissues. The HEK293 cell-based study revealed that the absence of CAMKK2-CAMK4 signaling altered intracellular Ca²⁺ homeostasis and lead to abnormal calcium signaling during TF trafficking. Also, CAMKK2-CAMK4 signaling deficiency affected the molecular interaction of TF and TF-receptor-associated protein complexes which indicated a potential failure in the recruitment of interacting proteins due to differential PTMs in TF.

Conclusion

Overall, this study established a novel mechanistic link between intracellular Ca²⁺ level, receptor-mediated TF trafficking, and iron homeostasis, all regulated by CAMKK2-CAMK4 signaling.

Application of information theory in systems biology

Over recent years, new light has been shed on aspects of information processing in cells. The quantification of information, as described by Shannon’s information theory, is a basic and powerful tool that can be applied to various fields, such as communication, statistics, and computer science, as well as to information processing within cells. It has also been used to infer the network structure of molecular species. However, the difficulty of obtaining sufficient sample sizes and the computational burden associated with the high-dimensional data often encountered in biology can result in bottlenecks in the application of information theory to systems biology. This article provides an overview of the application of information theory to systems biology, discussing the associated bottlenecks and reviewing recent work.

Relevance of Hydrogen Bonds for the Histamine H2 Receptor-Ligand Interactions: A Lesson from Deuteration

We used a combination of density functional theory (DFT) calculations and the implicit quantization of the acidic N–H and O–H bonds to assess the effect of deuteration on the binding of agonists (2-methylhistamine and 4-methylhistamine) and antagonists (cimetidine and famotidine) to the histamine H2 receptor. The results show that deuteration significantly increases the affinity for 4-methylhistamine and reduces it for 2-methylhistamine, while leaving it unchanged for both antagonists, which is found in excellent agreement with experiments. The revealed trends are interpreted in the light of the altered strength of the hydrogen bonding upon deuteration, known as the Ubbelohde effect, which affects ligand interactions with both active sites residues and solvent molecules preceding the binding, thus providing strong evidence for the relevance of hydrogen bonding for this process. In addition, computations further underline an important role of the Tyr250 residue for the binding. The obtained insight is relevant for the therapy in the context of (per)deuterated drugs that are expected to enter therapeutic practice in the near future, while this approach may contribute towards understanding receptor activation and its discrimination between agonists and antagonists.

Individual Cells Can Resolve Variations in Stimulus Intensity along the IGF-PI3K-AKT Signaling Axis

Cells sense and respond to signals in their local environment by activating signaling cascades that lead to phenotypic changes. Differences in these signals can be discriminated at the population level; however, single cells have been thought to be limited in their capacity to distinguish ligand doses due to signaling noise. We describe here the rational development of a genetically encoded FoxO1 sensor, which serves as a down-stream readout of insulin growth factor-phosphatidylinositol 3-kinase IGF-PI3K-AKT signaling pathway activity. With this reporter, we tracked individual cell responses to multiple IGF-I doses, pathway inhibitors, and repeated treatments. We observed that individual cells can discriminate multiple IGF-I doses, and these responses are sustained over time, are reproducible at the single-cell level, and display cell-to-cell heterogeneity. These studies imply that cell-to-cell variation in signaling responses is biologically meaningful and support the endeavor to elucidate mechanisms of cell signaling at the level of the individual cell.

Universality of fold-encoded localized vibrations in enzymes

Enzymes speed up biochemical reactions at the core of life by as much as 15 orders of magnitude. Yet, despite considerable advances, the fine dynamical determinants at the microscopic level of their catalytic proficiency are still elusive. In this work, we use a powerful mathematical approach to show that rate-promoting vibrations in the picosecond range, specifically encoded in the 3D protein structure, are localized vibrations optimally coupled to the chemical reaction coordinates at the active site. Remarkably, our theory also exposes an hithertho unknown deep connection between the unique localization fingerprint and a distinct partition of the 3D fold into independent, foldspanning subdomains that govern long-range communication. The universality of these features is demonstrated on a pool of more than 900 enzyme structures, comprising a total of more than 10,000 experimentally annotated catalytic sites. Our theory provides a unified microscopic rationale for the subtle structure-dynamics-function link in proteins.

Intrinsic limits of information transmission in biochemical signalling motifs

All living things have evolved to sense changes in their environment in order to respond in adaptive ways. At the cellular level, these sensing systems generally involve receptor molecules at the cell surface, which detect changes outside the cell and relay those changes to the appropriate response elements downstream. With the advent of experimental technologies that can track signalling at the single-cell level, it has become clear that many signalling systems exhibit significant levels of 'noise,' manifesting as differential responses of otherwise identical cells to the same environment. This noise has a large impact on the capacity of cell signalling networks to transmit information from the environment. Application of information theory to experimental data has found that all systems studied to date encode less than 2.5 bits of information, with the majority transmitting significantly less than 1 bit. Given the growing interest in applying information theory to biological data, it is crucial to understand whether the low values observed to date represent some sort of intrinsic limit on information flow given the inherently stochastic nature of biochemical signalling events. In this work, we used a series of computational models to explore how much information a variety of common 'signalling motifs' can encode. We found that the majority of these motifs, which serve as the basic building blocks of cell signalling networks, can encode far more information (4-6 bits) than has ever been observed experimentally. In addition to providing a consistent framework for estimating information-theoretic quantities from experimental data, our findings suggest that the low levels of information flow observed so far in living system are not necessarily due to intrinsic limitations. Further experimental work will be needed to understand whether certain cell signalling systems actually can approach the intrinsic limits described here, and to understand the sources and purpose of the variation that reduces information flow in living cells.